Development of neural network potential for Al-based alloys containing vacancy
Author:
Affiliation:
1. Graduate School of Advanced Science and Engineering, Hiroshima University
Publisher
Japan Society of Mechanical Engineers
Subject
Process Chemistry and Technology,Economic Geology,Fuel Technology
Link
https://www.jstage.jst.go.jp/article/mej/10/4/10_23-00066/_pdf
Reference17 articles.
1. Binglun Yin and William A Curtin,First-principles-based prediction of yield strength in the RhIrPdPtNiCu high-entropy alloy, npj Computational Materials,Vol.5,No.1 (2019), pp.1-7.
2. David Vanderbilt,Soft self-consistent pseudopotentials in a generalized eigenvalue formalism,Physical review B, Vol.41, No.11 (1990), p.7892.
3. Diederik P Kingma and Jimmy Ba,Adam: a method for stochastic optimization (2014), arXiv preprint (2014). DOI:10.48550/arXiv.1412.6980.
4. Fang-Qin Ren, et al.,Density Functional study of the structural, stability, magnetic properties and chirality of small-sized Al X Zr Y (X+ Y≤ 9) alloy clusters,Journal of Theoretical and Computational Chemistry, Vol.16, No.07 (2017), p.1750058.
5. Feng-xiang Liu, et al.,Formation mechanism of atomic cluster structures in Al–Mg alloy during rapid solidification processes,Annals of Physics, Vol.324, No.2 (2009), pp.332-342.
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